Functional spatial units are fundamental for modelling ecosystem services in mountain regions. (May 2020)
- Record Type:
- Journal Article
- Title:
- Functional spatial units are fundamental for modelling ecosystem services in mountain regions. (May 2020)
- Main Title:
- Functional spatial units are fundamental for modelling ecosystem services in mountain regions
- Authors:
- Schirpke, Uta
Leitinger, Georg
Tasser, Erich
Rüdisser, Johannes
Fontana, Veronika
Tappeiner, Ulrike - Abstract:
- Abstract: The application of ecosystem services (ES) models that rely on primary biophysical data is considered as most promising to generate accurate maps for decision making. However, to effectively apply these modelling approaches for ES mapping, representative functional spatial units with distinct socio-ecological characteristics are needed, which allow the upscaling of measured variables from the plot level to the landscape scale. In this study, we propose a theoretical framework for delineating functional spatial units based on abiotic and management variables. We apply this framework for an alpine grassland site and identify functional spatial units (here referred as to grassland trajectories) based on abiotic (elevation, slope, aspect) and management variables (fertilised or unfertilised) for three time steps (2015, 1953 and 1861). We test, via discriminant analyses, whether these grassland trajectories reflect variations in plant and soil traits. Our results indicate that the combination of topographical and management variables leads to significantly better classification results compared to land use/land cover (LULC) or topography alone. The best result could be obtained when information of past and present LULC was included, i.e. 51% of grassland trajectories were correctly classified. We finally use these grassland trajectories to map five ES (forage production and forage quality, carbon storage, water quality and soil fertility) based on trait-based models toAbstract: The application of ecosystem services (ES) models that rely on primary biophysical data is considered as most promising to generate accurate maps for decision making. However, to effectively apply these modelling approaches for ES mapping, representative functional spatial units with distinct socio-ecological characteristics are needed, which allow the upscaling of measured variables from the plot level to the landscape scale. In this study, we propose a theoretical framework for delineating functional spatial units based on abiotic and management variables. We apply this framework for an alpine grassland site and identify functional spatial units (here referred as to grassland trajectories) based on abiotic (elevation, slope, aspect) and management variables (fertilised or unfertilised) for three time steps (2015, 1953 and 1861). We test, via discriminant analyses, whether these grassland trajectories reflect variations in plant and soil traits. Our results indicate that the combination of topographical and management variables leads to significantly better classification results compared to land use/land cover (LULC) or topography alone. The best result could be obtained when information of past and present LULC was included, i.e. 51% of grassland trajectories were correctly classified. We finally use these grassland trajectories to map five ES (forage production and forage quality, carbon storage, water quality and soil fertility) based on trait-based models to exemplify the operational suitability of grassland trajectories to upscale plot-level data to the landscape scale. Current ES provision varies greatly for the different grassland trajectories, revealing the combined effects of abiotic and biotic drivers. Highlights: We propose a framework to delineate functional spatial units for ES mapping. We delineate grassland trajectories based on topography and current/past land use. We test whether grassland trajectories reflect variations in plant and soil traits. Grassland trajectories are essential to upscale plot-data to the landscape scale. We exemplarily map five ES of mountain grassland applying trait-based ES models. … (more)
- Is Part Of:
- Applied geography. Volume 118(2020)
- Journal:
- Applied geography
- Issue:
- Volume 118(2020)
- Issue Display:
- Volume 118, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 118
- Issue:
- 2020
- Issue Sort Value:
- 2020-0118-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-05
- Subjects:
- Mountain grassland -- Functional traits -- Spatial heterogeneity -- Biophysical indicators -- Ecological units
Geography -- Periodicals
Human geography -- Periodicals
Human ecology -- Periodicals
910 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.apgeog.2020.102200 ↗
- Languages:
- English
- ISSNs:
- 0143-6228
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1572.590000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 13379.xml